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Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense
Summary: ADGNN: active defense for dynamic graphs that injects optimizable guardian nodes to disrupt attackers' node-injection strategies. Optimizes an active-defense objective via a gradient-based algorithm with two speedups, outperforming passive pattern-specific defenders and augmenting existing GNN defenses.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13439
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 4.4909322e-05
- Overall Rank
- 8,507 | 40.88%
- DOI
-
10.14778/3659437.3659457
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 635 |
APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding |
2021 |
SIGMOD |
0.00018825777 |
| 2,399 |
ByteGNN: Efficient Graph Neural Network Training at Large Scale |
2022 |
VLDB |
8.8869693e-05 |
| 2,901 |
ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network |
2021 |
VLDB |
7.9448215e-05 |
| 3,370 |
Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed |
2022 |
VLDB |
7.1645471e-05 |
| 3,715 |
Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank |
2023 |
VLDB |
6.8176818e-05 |
| 3,805 |
Scaling Attributed Network Embedding to Massive Graphs |
2021 |
VLDB |
6.7485579e-05 |
| 3,882 |
Building Enclave-Native Storage Engines for Practical Encrypted Databases |
2021 |
VLDB |
6.6636559e-05 |
| 3,988 |
G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs |
2020 |
VLDB |
6.5548465e-05 |
| 4,054 |
Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees |
2023 |
SIGMOD |
6.4910804e-05 |
| 4,126 |
Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization |
2021 |
VLDB |
6.4242e-05 |
| 4,206 |
Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting |
2022 |
VLDB |
6.3534357e-05 |
| 5,431 |
SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization |
2022 |
VLDB |
5.5104776e-05 |
| 5,452 |
Decoupled Graph Neural Networks for Large Dynamic Graphs |
2023 |
VLDB |
5.4972958e-05 |
| 5,485 |
ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs |
2024 |
VLDB |
5.4817019e-05 |
| 5,499 |
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys |
2022 |
SIGMOD |
5.4737427e-05 |
| 5,530 |
Efficient Streaming Subgraph Isomorphism with Graph Neural Networks |
2021 |
VLDB |
5.4562393e-05 |
| 5,899 |
METRO: A Generic Graph Neural Network Framework for Multivariate Time Series Forecasting |
2022 |
VLDB |
5.2806419e-05 |
| 6,479 |
EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs |
2023 |
SIGMOD |
5.0405101e-05 |
| 6,719 |
Operon: An Encrypted Database for Ownership-Preserving Data Management |
2022 |
VLDB |
4.9458096e-05 |
| 7,059 |
Residual Sensitivity for Differentially Private Multi-Way Joins |
2021 |
SIGMOD |
4.8404261e-05 |
| 7,286 |
DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning |
2024 |
VLDB |
4.7701372e-05 |
| 7,584 |
A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries |
2022 |
PODS |
4.7015411e-05 |
| 9,277 |
Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs |
2023 |
VLDB |
4.3610659e-05 |
| 9,596 |
Scalable Graph Convolutional Network Training on Distributed-Memory Systems |
2023 |
VLDB |
4.3150788e-05 |
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5.1779507e-05 |
| 3,370 |
Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed |
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7.1645471e-05 |
| 3,092 |
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SIGMOD |
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VLDB |
4.8875946e-05 |
| 6,479 |
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2023 |
SIGMOD |
5.0405101e-05 |
| 5,452 |
Decoupled Graph Neural Networks for Large Dynamic Graphs |
2023 |
VLDB |
5.4972958e-05 |